Collaboration across countries

Q: How are authorship roles distributed with international collaborations?

Only take into account papers with more than one country on it.

author_paper_affiliations_w_groups <- make_author_groups(author_paper_affiliations)

collaborative_papers <- papers %>% 
  select(paperid, year) %>% 
  left_join(author_paper_affiliations_w_groups) %>% 
  left_join(affils) %>% 
  group_by(paperid) %>% 
  # check if we have country for all authors
  mutate(country_available = sum(as.numeric(is.na(country))) == 0) %>% 
  filter(country_available, paper_author_cat == "multi") %>% 
  select(paperid, year, country, paper_author_cat, author_position)
## Joining, by = "paperid"
## Joining, by = "affiliationid"
collaboration_by_country <- collaborative_papers %>% 
  group_by(country) %>% 
  count(author_position) %>% 
  collect()

# then join with WDI, 
collaborative_countries <- collaboration_by_country %>% 
  left_join(wb_countries_selected, by = c("country" = "Country Code"))

# only keep countries where each position has at least 5 papers
collaborative_countries <- collaborative_countries %>% 
  group_by(country) %>% 
  mutate(include = all(n >= 5)) %>% 
  ungroup()
# then plot by income region and geographical region
plot_countries <- function(df, facet) {
  pdata <- df %>% 
    group_by({{facet}}) %>% 
    add_proportion(n, order_var = author_position,
                   order_string = "first") %>% 
    drop_na() %>% 
    mutate(author_position = fct_relevel(author_position, "first_author", 
                                         after = 2))
  
  pdata %>% 
    ggplot(aes(fct_reorder({{facet}}, order), prop, fill = author_position)) +
    geom_col(width = .7) +
    scale_y_continuous(labels = scales::percent) +
    coord_flip() +
    labs(x = NULL, y = "% of authorship positions", fill = NULL,
         caption = "Only considering papers with at least three authors.") +
    theme(legend.position = "top") +
    guides(fill = guide_legend(reverse = TRUE))
}


plot_countries(collaborative_countries, Region) +
  labs(title = "Authorship positions by geographic region")

plot_countries(collaborative_countries, `Income Group`) +
  labs(title = "Authorship positions by country income")

Overall, there are no big differences. The hypothesis that LIC are driven towards certain positions is not observable from this view. Maybe this is true if we look at papers which have been published in certain journals, i.e. in higher prestige journals. Because the underlying hypothesis would have been: authorship positions from LIC for papers led by WEIRD researchers.

But maybe this underlying hypothesis is very biased and dismissive of researchers from other continents?

p <- collaborative_countries %>% 
  filter(include) %>% 
  plot_countries(`Short Name`) +
  labs(title = "Authorship position by country", 
       subtitle = "")
plotly::ggplotly(p)

This again is only considering papers with at least three authors and countries with at least 5 papers per position.

collaborative_countries %>% 
  mutate(Region = fct_relevel(Region, "North America", "South Asia", after = 5)) %>% 
  filter(include) %>% 
  plot_countries(`Short Name`) +
  facet_wrap(vars(Region), scales = "free_y", ncol = 2)

Remaining questions to cover